The field of the disclosure relates generally to structural health monitoring, and more specifically, to systems and methods for providing temperature compensation in structural health monitoring.
Many structural health monitoring (SHM) systems operate by producing a vibration signal, for example by exciting a piezo-electric (PZT) actuator bonded to a structure, and then reading that signal with a PZT sensor bonded at a separate location. Any damage that has occurred between the two PZT transducers will change the characteristics of the transmitted signal, as compared to the characteristics of a transmitted signal where no damage has occurred between the two transducers.
Many SHM algorithms work in the time domain by comparing a reference, or baseline, signal with a comparison signal that may be indicative of damage. In a properly operating SHM system, the degree of difference between the two signals is proportional to the size of damage in the structure. Examples of damage in such structures include a crack having a length or a delamination area within the structure.
Although there are many ways to measure the difference between two signals, normalized RMS error is one very common measure. The RMS error is calculated by subtracting the comparison signal from the reference signal forming an error signal. Each sample of this error signal is squared and summed. The result is divided by the number of samples to get the mean square value and the square root of this value is taken. This is the Root Mean Square or RMS of the error signal. This number is then normalized by the RMS value of the reference wave.
Unfortunately damage is not the only variable that can change a signal. A real world effect that strongly affects a signal is the temperature of the structure when the PZT actuator produces the signal and the PZT sensor measures the signal. One effect of temperature change is to stretch (heating) or compress (cooling) the signal with a secondary effect of distorting the shape of the signal. Due to this effect, the mean squared error between two waveforms recorded at temperatures only a few degrees apart is of the same order of magnitude as the mean squared error between waveforms recorded from a structure before and after damage.